A new approach to fuzzy modeling

Euntai Kim, Minkee Park, Seunghwan Ji, Mignon Park

Research output: Contribution to journalArticle

364 Citations (Scopus)

Abstract

This paper proposes a new approach to fuzzy modeling. The suggested fuzzy model can express a given unknown system with a few fuzzy rules as well as Takagi and Sugeno's model [1], because it has the same structure as that of Takagi and Sugeno's model. It is also as easy to implement as Sugeno and Yasukawa's model [2] because its identification mimics the simple identification procedure of Sugeno and Yasukawa's model. The suggested algorithm is composed of two steps: coarse tuning and fine tuning. In coarse tuning, fuzzy C-regression model (FCRM) clustering is used [3], which is a modified version of fuzzy C-means (FCM) [4]. In fine tuning, gradient descent algorithm is used to precisely adjust parameters of the fuzzy model instead of nonlinear optimization methods used in other models. Finally, some examples are given to demonstrate the validity of this algorithm.

Original languageEnglish
Pages (from-to)328-337
Number of pages10
JournalIEEE Transactions on Fuzzy Systems
Volume5
Issue number3
DOIs
Publication statusPublished - 1997 Dec 1

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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